{"id":"https://openalex.org/W4409870639","doi":"https://doi.org/10.1177/14727978241299599","title":"A noise self-training insulator-defect detection method based on the improved two-stage detection net with data generation","display_name":"A noise self-training insulator-defect detection method based on the improved two-stage detection net with data generation","publication_year":2024,"publication_date":"2024-11-11","ids":{"openalex":"https://openalex.org/W4409870639","doi":"https://doi.org/10.1177/14727978241299599"},"language":"en","primary_location":{"id":"doi:10.1177/14727978241299599","is_oa":false,"landing_page_url":"https://doi.org/10.1177/14727978241299599","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108240685","display_name":"Lizhu Liu","orcid":"https://orcid.org/0000-0001-5454-4810"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lizhu Liu","raw_affiliation_strings":["Shenzhen Grid Co., Ltd","Shenzhen Grid Co., Ltd., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Grid Co., Ltd","institution_ids":[]},{"raw_affiliation_string":"Shenzhen Grid Co., Ltd., Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109568711","display_name":"Wendy Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wanyi Wu","raw_affiliation_strings":["Shenzhen Grid Co., Ltd","Shenzhen Grid Co., Ltd., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Grid Co., Ltd","institution_ids":[]},{"raw_affiliation_string":"Shenzhen Grid Co., Ltd., Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021765493","display_name":"PingAn Hu","orcid":"https://orcid.org/0000-0003-3499-2733"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pochen Hu","raw_affiliation_strings":["Wuhan University","School of Electrical Engineering and Automation, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Electrical Engineering and Automation, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064369518","display_name":"Yitao Li","orcid":"https://orcid.org/0000-0001-7496-2956"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yitao Li","raw_affiliation_strings":["Wuhan University","School of Electrical Engineering and Automation, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Electrical Engineering and Automation, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5021765493"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2737234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"1","first_page":"67","last_page":"83"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10511","display_name":"High voltage insulation and dielectric phenomena","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.6562814712524414},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6050962209701538},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.46210822463035583},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46116796135902405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4388793706893921}],"concepts":[{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.6562814712524414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6050962209701538},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.46210822463035583},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46116796135902405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4388793706893921},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/14727978241299599","is_oa":false,"landing_page_url":"https://doi.org/10.1177/14727978241299599","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1981025032","https://openalex.org/W1983320747","https://openalex.org/W2095705004","https://openalex.org/W2194775991","https://openalex.org/W2613718673","https://openalex.org/W2883668949","https://openalex.org/W2963351448","https://openalex.org/W3005809051","https://openalex.org/W3035160371","https://openalex.org/W3035574324","https://openalex.org/W3124139589","https://openalex.org/W3138967436","https://openalex.org/W3176913662","https://openalex.org/W3193476445","https://openalex.org/W3206532283","https://openalex.org/W4283021596","https://openalex.org/W4287322212","https://openalex.org/W4294496097","https://openalex.org/W4310127911","https://openalex.org/W4319922489","https://openalex.org/W4327624012","https://openalex.org/W4384130825","https://openalex.org/W4387407965"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Traditional":[0],"methods":[1],"for":[2,114],"detecting":[3],"damage":[4],"of":[5,17,20,27,76,171],"electric":[6],"power":[7],"line":[8],"insulators":[9],"are":[10,129,136],"often":[11],"limited":[12],"to":[13,71,88,97,109,177],"improve":[14],"the":[15,25,58,66,89,99,111,115,139,147,151,156,160,168,172],"accuracy":[16,170],"detection":[18,38,45,62],"because":[19],"poor":[21],"datasets.":[22],"To":[23],"enhance":[24],"performance":[26],"insulator":[28],"detectors,":[29],"in":[30],"this":[31,104],"paper,":[32],"we":[33],"propose":[34],"a":[35,42,73,84,92],"semi-supervised":[36,179],"object":[37],"method":[39],"by":[40,83],"combining":[41],"two-stage":[43],"proposal-connection":[44],"net":[46],"(TPD-Net)":[47],"with":[48],"an":[49],"enhanced":[50],"network":[51,55,63],"structure":[52],"generative":[53],"adversarial":[54],"(En-GAN),":[56],"termed":[57],"noise":[59,119],"self-training":[60,120],"insulator-defect":[61],"(NS-IDNet).":[64],"Firstly,":[65],"En-GAN":[67],"approach":[68],"is":[69,95,107,121,175],"utilized":[70],"synthesize":[72],"large":[74],"number":[75],"class-balanced":[77],"samples":[78],"as":[79],"unlabeled":[80,116],"data,":[81,101],"controlled":[82],"coefficient.":[85],"Secondly,":[86],"according":[87],"TPD-Net":[90],"method,":[91],"teacher":[93,105,127],"model":[94,106,125,128],"trained":[96,131],"employ":[98],"labeled":[100],"and":[102,126,142],"then":[103],"used":[108],"predict":[110],"sample":[112],"labels":[113],"data.":[117],"Finally,":[118],"conducted.":[122],"The":[123],"student":[124],"repeatedly":[130],"until":[132],"convergence,":[133],"while":[134],"noises":[135],"introduced":[137],"into":[138],"above":[140],"models":[141],"samples.":[143],"Diagnostic":[144],"results":[145],"on":[146],"test":[148],"set":[149],"from":[150],"original":[152],"dataset":[153],"reveal":[154],"that":[155],"proposed":[157,173],"NS-IDNet":[158,174],"outperforms":[159],"traditional":[161,178],"supervised":[162],"model.":[163],"Additionally,":[164],"comparative":[165],"experiments":[166],"demonstrate":[167],"diagnostic":[169],"superior":[176],"models.":[180]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
